Research on Reliability of Online Monitoring Results of Factory Discharge Pollutant SO<sub>2</sub> Based on Regression Analysis

Yang Shuo; Pan Zhiqiang; Niu Xingrong; Geng Lei; Sun Zhijing; Ma Dongchang; Wang Douwen

doi:doi:10.11648/j.ijmea.20231103.12

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Research on Reliability of Online Monitoring Results of Factory Discharge Pollutant SO₂ Based on Regression Analysis

Yang Shuo, Pan Zhiqiang, Niu Xingrong, Geng Lei, Sun Zhijing, Ma Dongchang, Wang Douwen

Published in International Journal of Mechanical Engineering and Applications (Volume 11, Issue 3)

Received: 18 June 2023 Accepted: 10 July 2023 Published: 4 August 2023

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Abstract

Concerning the SO₂ pollution source monitoring, discussed and even debated all the time, is in the environmental field. Adhere to purpose of "lucid waters and lush mountains are invaluable assets", the immediate task is to establish a complete and correct QA/QC monitoring system. In China, there are a large number of online devices, for its superiority compared with the laboratory technology, that undertake tests. However, it also has to be admitted that, the online system, belonging to a non-standard, shall paid more attention to its effectiveness. In this paper, a Deming regression technique of variable error model, with unbiased correction (CSS₀), constant bias correction (CSS₁) and linear bias correction (CSS₂) step by step, is used to fit at levels between online and its standard system. F and t, as well as χ2 distribution test are subsequently followed by for the selected CSS. Finally, under the independent identical distribution (i.i.d) condition based on the bias correction, use A* test to predict series residuals, from the correction, for its i.i.d condition. The uncertainty assessment, brought by the correction under site precision, combines the various variation to the maximum extent, and avoid the complicated correlation, is helpful for the quality assurance of the online system.

Published in	International Journal of Mechanical Engineering and Applications (Volume 11, Issue 3)
DOI	10.11648/j.ijmea.20231103.12
Page(s)	66-73
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2023. Published by Science Publishing Group

Keywords

Deming’s Regression, Closeness Sum of Squares, Weighted Fitting, Residuals, s_R’, A* Test

References

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[2]	ASTM D6299-2022el: Standard Practice for Applying Statistical Quality Assurance Techniques to Evaluate Analytical Measurement System Performances, ASTM International, West Conshohocken, PA, 2010, www.astm.org.
[3]	ASTM D6617-2021: Standard Practice for Laboratory Bias Detection Using Single Test Result from Standard Material, ASTM International, West Conshohocken, PA, 2010, www.astm.org.
[4]	ASTM D6792-2023a: Standard Practice for Quality Management Systems in Petroleum Products, Liquid Fuels, and Lubricants Testing Laboratories, ASTM International, West Conshohocken, PA, 2010, www.astm.org.
[5]	CNAS-GL016-2020: Guidance and illustration on Uncertainty Estimation in Physical and Chemical Testing in the Field of Petroleum and Petrochemicals, China National Accreditation Service for Conformity Assessment, Beijing, www.cnas.org.cn
[6]	Yang Shuo, Pan ZhiQiang Pan, Wang Dou Wen. Uncertainty Evaluation of Automatic Monitoring System for Fine Particulate Matter in Ambient Air, International Journal of Mechanical Engineering and Applications, Vol. 9, No. 6, 2021, pp. 95-98.
[7]	Zeng Xing-yu, et al. Evaluation of Uncertainty in Determination of Total Organic Carbon in Concentrated Seawater by Using Control Chart in Top-down. Contemporary Chemical Industry, 2021, 50 (1), pp. 95-1252.
[8]	Wang Qiang, et al. Uncertainty evaluation of determination of components in natural gas by using Top-down method. Chemical Engineering of Oil $ Gas, 2020, 48 (3), pp. 98-103.
[9]	Gao Huan, et al. Measurement Uncertainty for Unwashed Gum Content of Gasoline by Top-down Method. Guang Dong Chemical, 2021, 48 (9), pp. 263-267.
[10]	Cao Yiqun, et al. Estimation of Measurement Uncertainty of AFB by Top-down. Farm Products Processing, 2020, 1 (1), pp. 51-52.
[11]	Zhang Jifei, et al. Estimation of Measurement Uncertainty for Determination of Lead in Plastic Toys by X-ray fluorescence spectrometer based on Top-down method. Quality Safety Inspection and Testing, 2021, 31 (2), pp. 6-8.
[12]	ASTM D3764-2022: Standard Practice for Validation of the Performance of Process Stream Analyzer Systems, ASTM International, West Conshohocken, PA, 2010, www.astm.org.
[13]	ASTM D6122-2022: Standard Practice for Validation of the Performance of Multivariate Online, At-Line, Field and Laboratory Infrared Spectrophotometer, and Raman Spectrometer Based Analyzer Systems, ASTM International, West Conshohocken, PA, 2010, www.astm.org.
[14]	ASTM D7235-2021a: Standard Guide for Establishing a Linear Correlation Relationship Between Analyzer and Primary Test Method Results Using Relevant ASTM Standard Practices, ASTM International, West Conshohocken, PA, 2010, www.astm.org.
[15]	ASTM D7808-2022: Standard Practice for Determining the Site Precision of a Process Stream Analyzer on Process Stream Material, ASTM International, West Conshohocken, PA, 2010, www.astm.org.

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APA Style

Yang Shuo, Pan Zhiqiang, Niu Xingrong, Geng Lei, Sun Zhijing, et al. (2023). Research on Reliability of Online Monitoring Results of Factory Discharge Pollutant SO2 Based on Regression Analysis. International Journal of Mechanical Engineering and Applications, 11(3), 66-73. https://doi.org/10.11648/j.ijmea.20231103.12

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ACS Style

Yang Shuo; Pan Zhiqiang; Niu Xingrong; Geng Lei; Sun Zhijing, et al. Research on Reliability of Online Monitoring Results of Factory Discharge Pollutant SO2 Based on Regression Analysis. Int. J. Mech. Eng. Appl. 2023, 11(3), 66-73. doi: 10.11648/j.ijmea.20231103.12

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AMA Style

Yang Shuo, Pan Zhiqiang, Niu Xingrong, Geng Lei, Sun Zhijing, et al. Research on Reliability of Online Monitoring Results of Factory Discharge Pollutant SO2 Based on Regression Analysis. Int J Mech Eng Appl. 2023;11(3):66-73. doi: 10.11648/j.ijmea.20231103.12

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@article{10.11648/j.ijmea.20231103.12,
  author = {Yang Shuo and Pan Zhiqiang and Niu Xingrong and Geng Lei and Sun Zhijing and Ma Dongchang and Wang Douwen},
  title = {Research on Reliability of Online Monitoring Results of Factory Discharge Pollutant SO2 Based on Regression Analysis},
  journal = {International Journal of Mechanical Engineering and Applications},
  volume = {11},
  number = {3},
  pages = {66-73},
  doi = {10.11648/j.ijmea.20231103.12},
  url = {https://doi.org/10.11648/j.ijmea.20231103.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijmea.20231103.12},
  abstract = {Concerning the SO2 pollution source monitoring, discussed and even debated all the time, is in the environmental field. Adhere to purpose of "lucid waters and lush mountains are invaluable assets", the immediate task is to establish a complete and correct QA/QC monitoring system. In China, there are a large number of online devices, for its superiority compared with the laboratory technology, that undertake tests. However, it also has to be admitted that, the online system, belonging to a non-standard, shall paid more attention to its effectiveness. In this paper, a Deming regression technique of variable error model, with unbiased correction (CSS0), constant bias correction (CSS1) and linear bias correction (CSS2) step by step, is used to fit at levels between online and its standard system. F and t, as well as χ2 distribution test are subsequently followed by for the selected CSS. Finally, under the independent identical distribution (i.i.d) condition based on the bias correction, use A* test to predict series residuals, from the correction, for its i.i.d condition. The uncertainty assessment, brought by the correction under site precision, combines the various variation to the maximum extent, and avoid the complicated correlation, is helpful for the quality assurance of the online system.},
 year = {2023}
}

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TY  - JOUR
T1  - Research on Reliability of Online Monitoring Results of Factory Discharge Pollutant SO2 Based on Regression Analysis
AU  - Yang Shuo
AU  - Pan Zhiqiang
AU  - Niu Xingrong
AU  - Geng Lei
AU  - Sun Zhijing
AU  - Ma Dongchang
AU  - Wang Douwen
Y1  - 2023/08/04
PY  - 2023
N1  - https://doi.org/10.11648/j.ijmea.20231103.12
DO  - 10.11648/j.ijmea.20231103.12
T2  - International Journal of Mechanical Engineering and Applications
JF  - International Journal of Mechanical Engineering and Applications
JO  - International Journal of Mechanical Engineering and Applications
SP  - 66
EP  - 73
PB  - Science Publishing Group
SN  - 2330-0248
UR  - https://doi.org/10.11648/j.ijmea.20231103.12
AB  - Concerning the SO2 pollution source monitoring, discussed and even debated all the time, is in the environmental field. Adhere to purpose of "lucid waters and lush mountains are invaluable assets", the immediate task is to establish a complete and correct QA/QC monitoring system. In China, there are a large number of online devices, for its superiority compared with the laboratory technology, that undertake tests. However, it also has to be admitted that, the online system, belonging to a non-standard, shall paid more attention to its effectiveness. In this paper, a Deming regression technique of variable error model, with unbiased correction (CSS0), constant bias correction (CSS1) and linear bias correction (CSS2) step by step, is used to fit at levels between online and its standard system. F and t, as well as χ2 distribution test are subsequently followed by for the selected CSS. Finally, under the independent identical distribution (i.i.d) condition based on the bias correction, use A* test to predict series residuals, from the correction, for its i.i.d condition. The uncertainty assessment, brought by the correction under site precision, combines the various variation to the maximum extent, and avoid the complicated correlation, is helpful for the quality assurance of the online system.
VL  - 11
IS  - 3
ER  -

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Author Information

Yang Shuo

Shahekou District Government Office, Dalian, China
Pan Zhiqiang

Operations Division of Westpac Petrochemical Company, Dalian, China
Niu Xingrong

China National Accreditation Service for Conformity Assessment, Beijing, China
Geng Lei

China National Accreditation Service for Conformity Assessment, Beijing, China
Sun Zhijing

Dalian Product Quality Inspection and Testing Institute Co., Ltd., Dalian, China
Ma Dongchang

Zhongren Guozhi (Beijing) Testing Technology Research Institute, Beijing, China
Wang Douwen

Customs Technology Center, Dalian, China

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APA Style

Yang Shuo, Pan Zhiqiang, Niu Xingrong, Geng Lei, Sun Zhijing, et al. (2023). Research on Reliability of Online Monitoring Results of Factory Discharge Pollutant SO2 Based on Regression Analysis. International Journal of Mechanical Engineering and Applications, 11(3), 66-73. https://doi.org/10.11648/j.ijmea.20231103.12

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ACS Style

Yang Shuo; Pan Zhiqiang; Niu Xingrong; Geng Lei; Sun Zhijing, et al. Research on Reliability of Online Monitoring Results of Factory Discharge Pollutant SO2 Based on Regression Analysis. Int. J. Mech. Eng. Appl. 2023, 11(3), 66-73. doi: 10.11648/j.ijmea.20231103.12

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AMA Style

Yang Shuo, Pan Zhiqiang, Niu Xingrong, Geng Lei, Sun Zhijing, et al. Research on Reliability of Online Monitoring Results of Factory Discharge Pollutant SO2 Based on Regression Analysis. Int J Mech Eng Appl. 2023;11(3):66-73. doi: 10.11648/j.ijmea.20231103.12

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@article{10.11648/j.ijmea.20231103.12,
  author = {Yang Shuo and Pan Zhiqiang and Niu Xingrong and Geng Lei and Sun Zhijing and Ma Dongchang and Wang Douwen},
  title = {Research on Reliability of Online Monitoring Results of Factory Discharge Pollutant SO2 Based on Regression Analysis},
  journal = {International Journal of Mechanical Engineering and Applications},
  volume = {11},
  number = {3},
  pages = {66-73},
  doi = {10.11648/j.ijmea.20231103.12},
  url = {https://doi.org/10.11648/j.ijmea.20231103.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijmea.20231103.12},
  abstract = {Concerning the SO2 pollution source monitoring, discussed and even debated all the time, is in the environmental field. Adhere to purpose of "lucid waters and lush mountains are invaluable assets", the immediate task is to establish a complete and correct QA/QC monitoring system. In China, there are a large number of online devices, for its superiority compared with the laboratory technology, that undertake tests. However, it also has to be admitted that, the online system, belonging to a non-standard, shall paid more attention to its effectiveness. In this paper, a Deming regression technique of variable error model, with unbiased correction (CSS0), constant bias correction (CSS1) and linear bias correction (CSS2) step by step, is used to fit at levels between online and its standard system. F and t, as well as χ2 distribution test are subsequently followed by for the selected CSS. Finally, under the independent identical distribution (i.i.d) condition based on the bias correction, use A* test to predict series residuals, from the correction, for its i.i.d condition. The uncertainty assessment, brought by the correction under site precision, combines the various variation to the maximum extent, and avoid the complicated correlation, is helpful for the quality assurance of the online system.},
 year = {2023}
}

Copy | Download

TY  - JOUR
T1  - Research on Reliability of Online Monitoring Results of Factory Discharge Pollutant SO2 Based on Regression Analysis
AU  - Yang Shuo
AU  - Pan Zhiqiang
AU  - Niu Xingrong
AU  - Geng Lei
AU  - Sun Zhijing
AU  - Ma Dongchang
AU  - Wang Douwen
Y1  - 2023/08/04
PY  - 2023
N1  - https://doi.org/10.11648/j.ijmea.20231103.12
DO  - 10.11648/j.ijmea.20231103.12
T2  - International Journal of Mechanical Engineering and Applications
JF  - International Journal of Mechanical Engineering and Applications
JO  - International Journal of Mechanical Engineering and Applications
SP  - 66
EP  - 73
PB  - Science Publishing Group
SN  - 2330-0248
UR  - https://doi.org/10.11648/j.ijmea.20231103.12
AB  - Concerning the SO2 pollution source monitoring, discussed and even debated all the time, is in the environmental field. Adhere to purpose of "lucid waters and lush mountains are invaluable assets", the immediate task is to establish a complete and correct QA/QC monitoring system. In China, there are a large number of online devices, for its superiority compared with the laboratory technology, that undertake tests. However, it also has to be admitted that, the online system, belonging to a non-standard, shall paid more attention to its effectiveness. In this paper, a Deming regression technique of variable error model, with unbiased correction (CSS0), constant bias correction (CSS1) and linear bias correction (CSS2) step by step, is used to fit at levels between online and its standard system. F and t, as well as χ2 distribution test are subsequently followed by for the selected CSS. Finally, under the independent identical distribution (i.i.d) condition based on the bias correction, use A* test to predict series residuals, from the correction, for its i.i.d condition. The uncertainty assessment, brought by the correction under site precision, combines the various variation to the maximum extent, and avoid the complicated correlation, is helpful for the quality assurance of the online system.
VL  - 11
IS  - 3
ER  -

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